Research questions:
Section 1 - Table 1 - [ ] For each LGA , which police region recorded maximum incidents? - [ ] How did the trend of incidents recorded in those police regions varied across the years.
Section 2
Section 3
data3 %>%
group_by(Year,Suburb) %>%
summarise(Total_Incidents = sum(Incidents_Recorded)) %>%
arrange(Year,desc(Total_Incidents)) %>%
slice_max(Total_Incidents,n = 10) %>%
mutate(Suburb1 = reorder_within(Suburb,Total_Incidents,Year)) %>%
ggplot(aes(x=Total_Incidents ,
y=Suburb1,
fill = Suburb)) +
geom_col() +
geom_text(aes(label = Total_Incidents)) +
scale_y_reordered() +
ylab("Suburb") +
xlab("No. of Incidents") +
ggtitle("Top 10 Suburb with most incidents recorded in each Years") +
facet_wrap(~Year,ncol = 1, scales = "free")
Top 10 Suburb with most incidents recorded
Top 10 Offences recorded
Top 10 Offfences Suburrb wise
Q4graoh <- data3 %>%
filter(Suburb %in% unique(Suburb_imp$Suburb)) %>%
group_by(Year,Suburb,Offence_Subdivision) %>%
summarise(Tot_incidents = sum(Incidents_Recorded)) %>%
slice_max(Tot_incidents,n = 2) %>%
ggplot(aes(x= as.numeric(Year),
y =Tot_incidents,
color = Offence_Subdivision)) +
geom_line() +
geom_point() +
scale_x_continuous() +
xlab("Year") +
ylab("Total_incidents") +
facet_wrap(~Suburb)
ggplotly(Q4graoh)